LoRA Fine-Tuned Stable Diffusion v1.5 for Text-to-Image
This repository hosts a LoRA fine-tuned version of the runwayml/stable-diffusion-v1-5
model for text-to-image generation using the peft
and diffusers
libraries. The model has been fine-tuned on custom captioned image datasets, resized to 512x512 resolution, and optimized for generating high-quality images from textual prompts.
Model Details
- Base Model: Stable Diffusion v1.5 (
runwayml/stable-diffusion-v1-5
) - Frameworks: ๐ค Diffusers, PEFT
- Task: Text-to-Image Generation
- Technique: LoRA (Low-Rank Adaptation)
- Image Size: 512x512
- Dataset: Custom images with text captions
How to Use the Model
Below is a sample code snippet showing how to load and use the model:
from diffusers import StableDiffusionPipeline
from peft import PeftModel
import torch
# Load base pipeline
pipe = StableDiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
torch_dtype=torch.float16
).to("cuda")
# Load the LoRA fine-tuned adapter
pipe.unet = PeftModel.from_pretrained(
pipe.unet,
"Aksh16/Text_to_img" # Replace with your actual Hugging Face repo path
).to("cuda")
# Generate image from prompt
prompt = "A magical landscape with glowing mushrooms and waterfalls"
image = pipe(prompt).images[0]
# Save the output
image.save("output.png")
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Base model
runwayml/stable-diffusion-v1-5